Why you should update predictive models

After writing my previous post, “How Often Should You Update Predictive Models”, it was appropriate to followup with a post regarding the consequences of not updating predictive models.
Predictive models use the patterns in historical and transactional data to identify risks and opportunities. Since the conditions and the environment are constantly changing the accuracy of predictive models need to be monitored. Once a predictive model no longer reflects reality it needs to be updated. Most of the time this is because the assumptions behind the model need to be updated.
Take for example a community bank. Internally every new transaction, deposit, withdrawal, application, or transfer creates new data. For most individuals, these transactions are occur several time every day, and that means you’re compiling thousands of new data points. Over time the customers environment is changes, this  is reflected in each data point collected. Did they get a raise or a new job? Is there car breaking down? So although this community bank may have a relatively modest customer base, their customers are experiencing change all the time.
Also, their are external changes that impact a customer’s behavior. For example interest rates change, new competitors enter markets, competitors invest in marketing, consumer confidence changes, and competitors merge. It makes sense then that they would need to update their predictive models to keep up with all of these changes. When these changes start to represent structural changes a new model needs to be developed.
For a typical community bank, strategic sales, marketing, and planning decisions happen at least once a quarter. If a bank doesn’t update their predictive models in preparation for these events, they are at a high risk of using obsolete information when making decisions.
What are the consequences of using this obsolete information?

  • Your pricing models don’t reflect changes in the competitive environment.
  • You recommend outdated products.
  • Your marketing material isn’t targeted at the right groups. They might not exist any more.
  • Your business development team begins chasing the wrong types of leads. For example, it might not be a profit environment to pursue new home mortgages.

So if you’re planning on making an investment in predictive analytics, make sure you consider the implications of using your data as well as the consequences of using outdated information.

August 14, 2013 News No comments yet

How Often to Update Predictive Models

Everyday new information is being created in your business. Your customers are buying more, subscribing or unsubscribing, and before you know it your customers today are seemingly different than the customer you had the day before.
As these new patterns emerage its important to periodically take time to investigate your data, update your predictive models, and challenge the assumptions about your business going forward. But how often should you do this? To answer that question, consider the following:

  • How often is my data changing?
  • How often do I plan on making decisions with the data?

(more…)

August 13, 2013 Featured Posts, News No comments yet

History of Predictive Analytics: Since 1689

Many people credit the rise of predictive analytics to the technological advances of the last 50 years. However, The history of predictive analytics starts in 1689. Its true that record keeping standards, relational databases, faster CPUs, and even newer technologies such as Hadoop and MapReduce have made predictive analytics an accessible tool for decision making. However, the history of predictive analytics show that it has been used for centuries.  (more…)

August 12, 2013 Featured Posts, News 2 comments

Predictive Analytics is Not a Crystal Ball

Its common to see predictive analytics as a sort of “crystal ball” for your business. This crystal ball image makes for great marketing. Unfortunately, predictive analytics is not a crystal ball.
It will not provide the correct prediction every time. Its primary purpose is to help you make better decisions by giving you the power to unlock the patterns inside your data. When performed correctly this gives you the ability to simplify decisions. When performed incorrectly it can spell disaster for your company.
Predictive analytics is both an art and science. It requires a combination of both empirical and subjective experience to verify that models reflect reality. This is why CAN takes into consideration three main aspects when building predictive models: Data, Theory, and Math. In our experience your predictive models will not reflect reality if all of three of these aspects are not held up.  (more…)

August 8, 2013 Featured Posts, News 1 comment

The New Frontier of Data Science

Most of us think of our world as having already been explored.  After all, the days of Magellan and Columbus are literally history, and today we can pull up Google Maps to view satellite and street-level images of every square mile of our planet within seconds.  The generations before us sailed new seas, crossed continents and mapped lands that were completely foreign to them.  Future generations will be exploring the cosmos and travelling to distant planets.  And so it seems as if there aren’t any bold new frontiers for the explorers of our time, but that’s not true.
We live in the digital age, discovering new frontiers using computers, data and the Internet.  This world is growing in complexity and we are venturing out to map it and settle it.   According to Google’s Eric Schmidt, we now create as much new data in 2 days, as we did from the dawn of civilization up to 2003.  We produce 5 exabytes of data every 2 days. (1 exabyte = 1000 petabytes = 1,000,000 terabytes)
This new landscape of data science can be as foreign and complex to many of us as the Great Plains were to the early settlers.  Where do we begin?  Where are we going and how do we get there?  What resources do we have to gain from this bold, new world? (more…)

January 29, 2013 News No comments yet

Predictive Analytics improves M&A Activity

There have always been two major ways to expand your business:  Grow it, or Buy it.  This brings up some interesting questions about which is more beneficial.  The correct answer is usually based on cost of customer acquisition and customer lifetime value.  Right now, with the cost of client acquisition being so high, companies are turning to buying distressed businesses.  One, it eliminates competition, and two, the customers can be acquired “on sale”.  While mergers and acquisitions are common across all industries, there seems to be a significant propensity for growth by buying in the banking industry.
The unique problem that is causing an increase in the ” buy them” thought process is that in banking their revenue generating power has dwindled with the decline of interest rates.   Not only that but as clients leave for competitors by natural attrition, there is a dire need for new customers.  Buying seems to solve both of these.
While it may solve the issue of new customers at a reduced cost, how to transfer the old customer base to the new bank has always been a major problem.  First, you have a bevy of new customers who have not gone through your buying process.  You have no idea who they are and why they are in the product they are in.  Secondly, you can fix problem number one by keeping the staff from the bought bank, but they’re not sure if the customers are in the correct products anymore either because they don’t know what products they have to sell. (more…)

January 22, 2013 News No comments yet

Rethinking Business Intelligence: Information or Decisions

Traditional business intelligence leaves executives with the same amount of work, but with even more information to sort through. The number of decisions, the unit of work, is not diminished.
Traditional Business Intelligence asks, “What information do you need to make better decisions?” The outcome is hopefully beautiful well designed reports and dashboard that support decisions.  The problem is that you still have to make decisions.
Decisions are work.  Having more information doesn’t reduce the amount of work required to make decisions. In fact, it makes decisions more work.  More information does not create less work.
The flaw is thinking that the business decisions are calculations. (more…)

January 21, 2013 News 1 comment

8 isn't enough. Why you need a better sales system.

How many products can the average salesperson keep in their head while they are making reccomendations to customers? You will be shocked to find on average it is only 8.  What if 8 isn’t enough?  What if you have more than 8?  What if you have twice that?  Ten times that?
If you have more than 8 products, when a member of your sales team calls on a current client, they only recommend the products that they are most familiar with.  You have provided them an entire playbook, and they use only a tiny fraction.  Unless, those 8 products just happen to be the correct product for a customer, your sales staff just put a client into the wrong product.  They assumed that everyone was like them.
Think about that for a second.  The whole point of cross-sell is to keep your clients happy and purchasing from you. Matching the wrong product with the wrong person means reduced satisfaction, frustration, and loss of loyalty.  On the balance sheet, you are losing income, not maximizing profitability, and your salespeople are misusing their time.  How do you improve this? (more…)

January 9, 2013 News 1 comment

On Entrepreneurship, Risk and Uncertainty

Entrepreneurs live with risk and uncertainty. They don’t have a choice. The future is up to them. They are responsible for their successes and failures, and success is never permanent.  Therefore, Entrepreneurs have to learn to handle the risk and uncertainty of having to be responsible for their company and employees.
I have been fortunate. I have spent the majority of my life as an entrepreneur. In fact, I have never had a “real job”. I started my first real company when I was in elementary school, and sold it when I was 20.  I have spent most of my life focused on building successful and sustainable companies.  My early start allowed me to adjust gradually to the risks and uncertainty of being an entrepreneur.
When I started I had nothing to lose. I started a business because the people I knew needed a service and I had time. Gradually, the risks and uncertainty increased. In order to increase profits I started to take on more and riskier projects. They required hiring more employees, purchasing more equipment, investing more money, and taking more risks. Over the years, I have been forced to learn to handle the risk and uncertainty of being an entrepreneur, both in the good and bad times.  I have made and lost money, employees, and capital.
In good times, I learned to stay paranoid. In High School, after getting overly confident I learned the importance of Andy Grove’s quote, “Success breeds complacency, complacency failure, only the paranoid survive.” (more…)

January 8, 2013 Featured Posts, News 3 comments

Why Customer Segmentation Analysis is Essential

Customer segmentation analysis is essential. No company has just one type of customer. Customer segmentation analysis allows you and your data to capture this reality. Capturing reality is a pre-requisite to using data to make decisions. Each customer segment needs to be understood, marketed to, and tracked.  Download our case study. 
It is time to stop thinking about your “customer” and start thinking about your “customers”. Don’t let your marketing and customer metrics, hide valuable facts and insight in aggregated data and averages. The next level of marketing analytics is to calculate and track metrics for each customer segment. Customer segmentation provides you a window through which to understand why people do what they do. This gives you enormous power when trying to improve customer lifetime value, increase customer loyalty, reduce the cost of customer acquisition.

(more…)

January 7, 2013 News No comments yet
Featured Posts – Click the Brain
Archives
CAN Jewels